Biomathematics and Statistics Scotland (BioSS) seeks a quantitative scientist who wants to develop a personal research profile and to apply statistical methodologies to problems in the food and agricultural sciences. You’ll play a key role in developing and applying cutting-edge statistical approaches to address problems in animal and plant health. You will join the EPIC consortium (https://www.epicscotland.org/), which is the Centre of Expertise funded by the Scottish Government to advise on the control of animal disease outbreaks.  In EPIC and in other projects, you’ll collaborate closely with applied scientists from leading UK research institutions, and interact with other quantitative experts from within and beyond BioSS.

 

The post is an excellent long-term career opportunity for a suitably qualified statistician or quantitative scientist, offering a stimulating route to build your portfolio of statistical experience and expertise and develop skills in inter-disciplinary working in the important field of One Health.  You will have the chance to advance your career in a supportive environment at BioSS as we continue to grow as a centre of quantitative applied research and consultancy.  We want you to build a personal portfolio of research, and to develop professionally; we will support you in these objectives.  BioSS is eligible to apply for UKRI funding, and we will be keen for the successful applicant to contribute to proposals. This is a permanent post based at BioSS in Edinburgh, with flexibility to work from other BioSS locations in Dundee or Aberdeen, or remotely from home.

 

BioSS is a member of the SEFARI (Scottish Environment, Food and Agriculture Research Institutes) collective (https://sefari.scot/); we have an international reputation for research, consultancy and training in statistics, mathematical modelling and bioinformatics.  BioSS offers a stimulating working environment, with over 50 staff and students at 4 locations across Scotland.

 

At BioSS, you’ll be part of a forward-thinking, diverse and supportive team of over 50 staff and students working across multiple statistics and modelling disciplines, collaborating on applications in plant & crop science, animal health & welfare, environmental science & ecology, and human health & nutrition. We value collaboration, innovation, and the continuous development of our team members. We’ve been awarded Investors in People Gold Status since 2019, and we’re committed to promoting diversity and inclusion.

 

Potential applicants may contact Dr Giles Innocent (Giles.Innocent@bioss.ac.uk) in confidence to discuss this position.

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Benefits offered

• 35 hour working week.
• Annual Leave: Generous entitlement of up to 40.5 days a year.
• Pension: Employer Contribution of 15% of salary into a Personal Pension Plan, with employee contribution flexibility.
• Self-managed hours and Flexible Working: options to structure your working time, in line with organisational needs, to define a healthy work life balance.
• Generous annual time allocation to support your personal development as a scientist.
• Employee Assistance Programme: A confidential service available to support employees and their families with work or personal problems. 

 

Main Purpose of Job           

The successful candidate will:

• Contribute statistical expertise to collaborative research projects in the fields of Animal and Plant Health.
• Contribute as a participant in the EPIC Centre of Expertise in Animal Disease Outbreaks (https://www.epicscotland.org/).
• Deliver statistical consultancy across a wide range of projects in Animal and Plant Health. 
• Develop a portfolio of personal research in applied statistics or at the interface between statistics, mathematical modelling and bioinformatics, motivated by quantitative problems encountered in collaborative projects.
• Help develop applications for funding and contribute to the resulting projects.

 

Main duties of post holder

The successful candidate will be expected to:

• Collaborate with scientists working in the EPIC Centre of Expertise.
• Work with BioSS Application leads to contribute quantitative expertise to collaborative projects.
• Identify and develop an area of personal research relevant to Animal Health and/or Plant Health.
• Represent BioSS at meetings with stakeholders from scientific and non-scientific backgrounds.
• Extend collaborative links with government agencies, NGOs, universities, research institutes and commercial organisations.
• Contribute to the development and delivery of BioSS training courses for scientists. 
• Support other staff in seeking and winning external funding for research and consultancy projects, especially where these create new opportunities for collaboration with other organisations.

 

Qualifications/Skills/Knowledge

 

We will be looking for the following ‘Essential’ and ‘Desirable’ attributes in candidates:

 

Essential

 

• A PhD in statistics or another very closely related discipline, or an MSc with commensurate post-qualification development and work experience. 
• Experience of development and use of modern statistical methods applied to real-world examples.  Examples of desirable areas of expertise are given below.
• Experience of collaborative working at the interface between statistics and biological sciences, evidenced by scientific journal and conference papers, preferably in a methodological field relevant to animal and/or plant health.
• Evidence of ability to initiate, manage and maintain scientific collaborations, and an ability to work independently.
• Enthusiasm for development and application of quantitative methods, and for collaborating with non-quantitative scientists working in other applied sciences.
• Strong general statistical skills, and an understanding of relevant topics including experimental design, repeated measures, mixed models, generalised linear models, multivariate analysis and computationally intensive methods.
• Excellent statistical programming ability in R or equivalent high-level statistical programming platform.
• Evidence of good written communication.
• Ability to give effective spoken presentations, to both quantitative and wider scientific audiences.

 

Desirable

 

• Different skills sets would fit the remit of the post, any of which would be desirable.  For example, experience in:
• Spatial or spatio-temporal statistical modelling;
• Multiple imputation and synthetic data generation;
• Latent variable modelling.
• Experience of communicating with government and commercial clients. 
• Experience of developing funding applications.

 

 

How to Apply

 

Applications should be made using the recruitment pages operated by our parent organization, The James Hutton Institute. 

 

To apply, please create an account and upload personal details along with 

• a CV, including as a minimum your education and employment history plus relevant scientific achievements,
• a covering letter/statement detailing why you consider yourself suitable for this post.

 

We reserve the right to disregard applications based on material we identify as AI generated.

 

The deadline for applications is 3rd November 2024. Interviews are expected to be held on 18th November 2024.

 

Other Notes

We will not consider the use of 3rd party recruitment agencies for the sourcing of candidates for this position.

The James Hutton Institute is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.  We encourage applications from underrepresented groups in STEM, particularly women, BAME and LGBTQ+.

The James Hutton Institute is happy to talk flexible working.

The James Hutton Institute is a: Stonewall Diversity Champion; Athena SWAN Bronze Status Holder; Disability Confident Committed Employer and a Living Wage Employer.